System and method for evaluating and diagnosing patients based on ocular responses

ABSTRACT

A system for quantifying and mapping visual salience to a visual stimulus, including a processor, software for receiving data indicative of a group of individual&#39;s ocular responses to a visual stimulus, software for determining a distribution of visual resources at each of at least two times for each of at least a portion of the individuals. The system further including software for determining and quantifying a group distribution of visual resources at each of the at least two times and software for generating a display of the group&#39;s distribution of visual resources to the visual stimulus.

FIELD OF THE INVENTION

The invention relates to eye tracking, and more specifically to a systemand method for the quantifying and mapping of visual salience to staticor dynamic visual stimuli.

BACKGROUND OF THE INVENTION

Devices exist to measure and record eye movements. While many variationsexist, eye tracking devices often include a camera attached to acomputer which focuses on one or both of an individual's eyes andrecords eye movement. Some of such devices use contrast to locate thecenter of the pupil and use infrared illumination to create one or morecorneal reflections, and relating the position of these points todetermine a fixation point of the eye.

Eye movement data is typically categorized as fixations, smooth pursuitmovements, saccades, or blinks. A fixation is said to occur when the eyegaze pauses in a certain position while a saccade is when one's gaze ismoving to another position. By measuring and recording these movements,eye tracking devices may be used to determine where on a two-dimensionalplane or image a viewer is looking and for how long. Further, the pathone's eyes followed over the image may also be determined.

Eye tracking devices have many applications including, for example,advertising and market research. As disclosed in U.S. Pat. No.6,712,468, eye tracking devices have been used to track the eyes of aperson viewing a webpage. Representations may then be generated to show,e.g., designers of the webpage which regions of the webpage were viewedand which regions were not.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide a system and methodfor quantifying and mapping visual salience of visual stimuli.

It is a further object of the present invention to provide a system andmethod for representing and quantifying the distribution of visualresources of groups of individuals in response to a visual stimulus. Itis also an object to provide a system and method for comparingindividuals or groups of individuals to a target group. It is also anobject to provide a system and method for representing and quantifyingthe distribution of visual resources of groups of individuals to adynamic visual stimulus to identify locations and times of heightenedattention to the visual stimulus.

Still another object of the present invention is to provide a system andmethod for comparing and quantifying the ocular responses anddistribution of visual resources to visual stimuli of individuals orgroups of individuals.

These and other objectives are achieved by providing a system forquantifying and mapping visual salience to a dynamic visual stimulus,including a processor, software executing on the processor for receivingdata indicative of a group of individual's ocular responses to a dynamicvisual stimulus, software executing on the processor for determining adistribution of visual resources at each of at least two times for eachof at least a portion of the individuals, software executing on theprocessor for determining a group distribution of visual resources ateach of the at least two times, and software executing on the processorfor generating a display of the group's distribution of visual resourcesto the dynamic visual stimulus.

In some embodiments, the software for determining a distribution ofvisual resources of the system determines each distribution based on thedata and a distribution of biological resources such as retinal cells,cortical magnification, or other. Also in some embodiments, the displayof the group's distribution of visual resources includes an area ofmaximal salience at each of the at least two times corresponding toareas of the visual stimulus, wherein the areas of maximal salience areextruded over time to represent an attentional funnel.

Further provided is a system for quantifying and mapping visual salienceto a static visual stimulus, including a processor, software executingon the processor for receiving data indicative of a group ofindividual's ocular responses to a static visual stimulus, softwareexecuting on the processor for determining a distribution of visualresources at each of at least two times for each of at least a portionof the individuals, software executing on said processor for determininga group distribution of visual resources at each of the at least twotimes, and software executing on the processor for generating athree-dimensional display of the group's distribution of visualresources to the static visual stimulus over time.

Further provided is a method for quantifying and mapping visual salienceto a visual stimulus, including the steps of receiving data indicativeof a group of individual's ocular responses to a visual stimulus,determining a distribution of visual resources at each of at least twotimes and for each of at least a portion of the individuals of thegroup, determining a group distribution of visual resources at each ofthe at least two times, and generating a display of the group'sdistribution of visual resources to the visual stimulus over time.

In some embodiments, the method includes the steps of receiving subjectdata indicative of a subject's ocular responses to the visual stimulus,determining at least one point of regard at each of the at least twotimes based on the subject data, generating a display of the subject'sat least one point of regard, and comparing a display of the subject'sat least one point of regard to the display of the group's distributionof visual resources to the visual stimulus.

Other objects, features and advantages according to the presentinvention will become apparent from the following detailed descriptionof certain illustrated embodiments when read in conjunction with theaccompanying drawings in which the same components are identified by thesame reference numerals.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system for quantifying and mapping visual salience.

FIG. 2 is data indicative of ocular responses to a visual stimulus.

FIG. 3 is a display of portions of a dynamic visual stimulus over timeand data indicative of ocular responses to the dynamic visual stimulus.

FIG. 4 is display of points of regard over time.

FIG. 5A is a coordinate display of data representing a point of regard.

FIG. 5B is another coordinate display of data representing the point ofregard shown in FIG. 5A.

FIG. 5C is a topographical display of the point of regard shown in FIGS.5A and 5B and an exemplary distribution of visual resources.

FIG. 5D is a two-dimensional display of the point of regard anddistribution of visual resources shown in FIG. 5C.

FIG. 6A is a topographical display of a group distribution of visualresources.

FIG. 6B is another display of the group distribution of visual resourcesshown in FIG. 6A.

FIGS. 7A-7H show an exemplary generation of display of a group'sdistribution of visual resources.

FIG. 8A is a screenshot of a display of a group's distribution of visualresources to a visual stimulus.

FIG. 8B is another screenshot of the display of a group's distributionof visual resources to the visual stimulus.

FIG. 9A is a screenshot of another display of a group's distribution ofvisual resources to a visual stimulus.

FIG. 9B is another screenshot of the display of the group's distributionof visual resources to the visual stimulus shown in FIG. 9A.

FIG. 9C is another screen shot of the display of the group'sdistribution of visual resources to the visual stimulus shown in FIGS.9A and 9B.

FIG. 9D is a screen shot of another display of a group's distribution ofvisual resources to the visual stimulus shown in FIGS. 9A-9C.

FIGS. 10A-10F show a quantification of statistically significantconvergences of visual resources.

FIGS. 11A-11F show a means by which to compare a group's distribution ofvisual resources to an individual's ocular responses.

FIG. 12 is a method for quantifying and mapping visual salienceemployable by the system shown in FIG. 1.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates an exemplary system for quantifying and mappingvisual salience. The system includes at least one processor 102.Processor 102 may be any type of device designed to receive and executesoftware programs, or that which is designed to be modified infunctionality by software programs. For example, the processor 102 maybe selected from a group consisting of digital signal processors,microcontrollers, and microprocessors, or a group consisting of fieldprogrammable gate arrays, and computer programmable logic devices. Thefunctionality associated with the processor 102 may be centralized ordistributed, whether locally or remotely.

The processor 102 includes software executing thereon for receiving dataindicative of a group of individual's ocular responses to a visualstimulus, e.g., visual stimulus 120. For example, the processor 102 mayreceive eye data 112 from any number of eye trackers 110 or eye trackingdevices. Each eye tracker 110 may be any device for tracking themovement of at least one eye of an individual (e.g., individual human orany other species/animal). For example, the eye tracker 110 may be aninfrared video-oculography eye tracking device. In some embodiments, theeye tracker 110 is a binocular eye tracker. Each eye tracker 110 maygenerate eye data 112 indicative of ocular responses such as eyemovements, direction, dilation, rotation and/or gaze.

Based on the eye data 112, the processor 102 may determine and/oridentify points of regard. A point of regard is a point at which an eyeand/or both eyes of an individual are focusing. A point of regard may beindicated as a coordinate in space (e.g., x, y, z) or a two-dimensionalcoordinate data (e.g., x, y) on a surface or visual stimulus portrayedon a surface. A point of regard may additionally be referenced with atime (t). Each point of regard may indicate a point of fixation or anypoint of at which an eye is focusing regardless of the length of time orfixation on the point.

In some embodiments, the system includes a visual stimulus 120. Thevisual stimulus 120 may be any visual stimulus such as a still image(e.g., print ad, webpage, painting, etc.), video imagery, or interactivemedia. In a preferred embodiment, the visual stimulus 120 is a dynamicvisual stimulus such as a video. The video may include any imagery,broadcast, recording and/or representation of visual images ofstationary or moving objects including, but not limited to, a motionpicture, a video game, and/or a recording of a live event. The video maybe embodied in any form of media such as film, video tape, DVD, CD-ROMand/or digital storage (e.g., storage 130). The visual stimulus 120 mayalso be a live event (e.g., theatrical performance, social interaction,training exercise, etc) or any representation thereof (either two- orthree-dimensional).

Some embodiments of the system further include software for receivingstimulus data 122 from the visual stimulus 120. The stimulus data 122may be, for example, data representing the visual stimulus 120 (e.g.,representation or video recording of a live event), a complete videovisual stimulus 120, or any portion of a visual stimulus 120 (e.g.,frames and/or screenshots).

The system may also include a storage 130. The storage 130 may becollocated with the processor 102 or may be remotely located, e.g., andaccessible via a communications network. The storage 130 may providetemporary storage for the processor 102 (e.g., random access memory)and/or permanent or semi-permanent data storage, e.g., for eye data 112or stimulus data 122. The system may further include any number ofdisplays 140. The display 140 may also be located either local or remoteto the processor 102. For example, the display 140 may be remotelylocated and receive data or information from the processor 102 via theInternet. As will be described below, data representing points ofregard, distributions of visual resources, and/or a group's distributionof visual resources and/or attention to the visual stimulus 120 may bepresented on the display 140.

FIG. 2 shows an exemplary table 200 of data indicative of ocularresponses to a visual stimulus, or eye data 112. It should be understoodthat the eye data 112 may be organized and/or maintained in any manneror format and that the table 200 is only exemplary. As such, the table200 may be organized in any manner such as in columns 210, 220, 230 asshown. In the present illustration, the data is referenced ascoordinates describing points of regard. For example, an x-value of 300is shown at 212 with a corresponding y-value of 111 at 222. Thecoordinate in the present example further includes a time value incolumn 230, e.g., referring to a time that the particular coordinate ofeye data 112 was sampled. The time value may further correspond to atime 232 of a visual stimulus 250. Any number of additional categories(e.g., columns) of eye data 112 may be represented such as a z-valuereferring to a distance for the point of regard.

As shown in FIG. 2, a point of regard in the table 200 may be mapped tothe visual stimulus 250. For example, the point of regard referenced at212 and 222 may be mapped to a point 254 on a portion of the visualstimulus, e.g., using a coordinate system 252. The coordinate system 252may, in some embodiments, relate to any video pixel coordinate system(e.g., 640×480 or 720×480). The portion of the visual stimulus 250 maybe a portion (e.g., frame or panel) corresponding to the time at whichthe point of regard was sampled.

The eye data 112 may include data sampled at any rate or frequency. Forexample, eye data 112 may be sampled from an individual at a samplingfrequency of 60 Hz, 512 Hz, 1000 Hz, or any other sampling frequency.The rate of visualization or presentation of eye data may be increasedor decreased as desired and/or adjusted based on a rate of change of thedynamic visual stimulus, e.g., 250. Both rates of analysis and rates ofpresentation of eye data may also be based on analysis of meaningfulsegments of video isolated for scrutiny. For example, if meaningfulevents in the stimuli occur at a rate of 30 times per second, rates ofsampling, analysis, and presentation could equal or exceed 30 Hz.

FIG. 3 shows a display 300 of several portions and/or frames of adynamic visual stimulus. As shown, the display 300 includes a time axis330 and any number of frames, e.g., 332, 334, corresponding to differenttimes of the dynamic visual stimulus. Further represented in the display300 are points of regard, e.g., 354, 356, 358, on the frame 332. Each ofthe points of regard may be determined from eye data 112 sampled fromdifferent individuals. Alternatively, each point of regard may bedetermined from different viewings of the same dynamic visual stimulusby one individual.

FIG. 4 shows a display 400 of points of regard over time. The display400 includes a coordinate system having an x-axis 410, y-axis 420, and atime axis 430. The system of the present invention includes software forgenerating a display of the at least one individual's response and/ordistribution of visual resources to the visual stimulus. In the presentexample, a scanpath for each of a group of individuals is displayed asindividual points of regard over time. For example, the display 400includes any number of representations or scanpaths, e.g., 452, 454,each pertaining to one individual's ocular responses to a dynamic orstatic visual stimulus over time. Alternatively, each scanpath mayrepresent ocular responses experienced by the same individual uponmultiple viewings of the same visual stimulus.

As shown, the present embodiment provides a unique means to presentocular response data of multiple individuals over time. By comparingeach of the scanpaths shown in FIG. 4, any number of divergences 460,480 and convergences 470 of visual salience may be identified. Adivergence represents a time in which viewer's visual resources are nothighly overlapping, e.g., when viewers watching the same visual stimulusare generally looking at different points or areas. A convergencerepresents a heightened attention to a corresponding area of the visualstimulus, i.e., where viewers' visual resources are highly overlapping.The display 400 may be a static display, e.g., depicting a distinctperiod or range of time, or a dynamic display. For example, the display400 may be a continuous display changing over time. In either format,individuals' points of regard, the duration of divergences andconvergences, and their orders over time, are advantageously presentedin a single display 400. In some embodiments, portions (e.g., frames) ofthe visual stimulus may be mapped to the data and included in thedisplay 400.

In one embodiment, an average point of regard may be determined bycalculating an average or mean of all points of regard at that time. Amean deviation from that point may also be determined and used to definea radius about the mean point of regard. A defined area may be displayedto indicate a mean area of regard or fixation at the particular time(not shown). Such areas calculated for each of a number of times mayfurther be extruded and/or connected to generate a three-dimensionalrepresentation of divergences and convergences in the visual stimulusover time. However, as will be described below, the present inventionincludes a further embodiment which takes into consideration biologicalfactors, such as the distribution of retinal cells in the eye.

Shown in FIG. 5A, a point of regard 502 may be displayed in atwo-dimensional coordinate system. Each coordinate may correspond to alocation on a portion of a visual stimulus. With respect to a dynamicvisual stimulus, each coordinate may refer to a location on the stimulusas it appears at a particular time. While a point of regard 502 mayindicate a point where an eye(s) is focused, such representation doesnot take into account that an individual's visual attention may beallocated according to a non-uniform distribution about each point ofregard. The system therefore includes software for determining adistribution of visual resources (e.g., visual attention) based on anon-uniform distribution.

FIG. 5B shows another display of the point of regard 502 for which adistribution of visual resources may be determined. The point of regard502 is shown with reference to an x-axis 510 and y-axis 520. Furtherincluded in the display is a z-axis 550 representing a value of relativesalience. A distribution of one's visual resources directed at or arounda particular point of regard may be determined by several differentmeans. One such means is to use an index of biological resources in theeye, such as an index of retinal cell (e.g., ganglion cell) distributionin the eye. Preferably, the effective (e.g., sampling) distribution ofretinal cells is used rather than the actual, anatomical distribution ofretinal cells for increased accuracy. Some embodiments of the presenttherefore include software for determining and/or receiving datarepresenting an effective distribution of retinal cells (e.g., ganglioncells) in an eye (or an approximation thereof). In some otherembodiments, other distribution functions are used such as adistribution of cortical magnification factor, rod photoreceptors or acombinatorial distribution.

In one embodiment, a calculation of effective distribution of retinalganglion cells is accomplished by first creating a density matrixdescribing the anatomical distribution of retinal ganglion cells (notshown). Next, a density matrix of the anatomical distribution of conephotoreceptors is created. A ratio of ganglion cells to conephotoreceptors across the entire retina is determined. The distributionof cone photoreceptors is then multiplied by the ratio to yield a map ofeffective retinal ganglion cells (not shown). Based on the viewer'sfield-of-view (e.g., field-of-interest, distance away from a plane offixation), the retinal field-of-view may be subdivided to include only aportion of interest. A density of visual resources (e.g., density ofcells) relative to the pixels or unit of viewing angle or unit ofinterest is thus determined. The distribution may then be doubled toprovide a distribution for both eyes of a given individual.

Using the distribution of retinal cells and a point of regard 502, adistribution of visual resources 560 centered about the point of regard502 may be generated and displayed topographically as shown in FIG. 5C.As shown in FIG. 5D, the distribution of visual resources 560 may alsobe shown two-dimensionally wherein the distribution is represented by acolor gradient or pseudo-color mapping. In some embodiments, thedistribution is shown as an overlay to the visual stimulus wherein agrayscale from black to transparent represents relative salience (notshown).

For any given time, any number of individual distributions of visualresources (e.g., 560) may be determined. For example, a distribution ofvisual resources may be determined for each point of regard from the eyedata 112 at any number of particular times (e.g., each pertaining to adifferent individual's ocular response at the given time). Eachdistribution of visual resources may pertain to a different individualviewing the same visual stimulus, or each may pertain to the sameindividual upon different viewings of the same visual stimulus.

The system according to the present invention further includes softwarefor determining a group distribution of visual resources at particulartimes. As shown in FIG. 6A, a group distribution of visual resources maybe determined and represented by aggregating any number of individualdistributions of visual resources (e.g., 660, 662, 664). Any means ofaggregating the distributions may be used. For example, the distributionfunctions may be summed linearly to determine the group distribution.Alternatively, the distribution functions may be multiplied. Based onthe group distribution of visual resources, an average (e.g., mean ormedian) value of relative salience 652 may be determined. Across-section of the group distribution of visual resources may be takenat the average value 652 to determine an area or region of maximalsalience at the particular time. The area of maximal salience at eachparticular time according to the present embodiment is thereforedetermined by the viewers and their distributions of visual resources,rather than by an approximation based on the locations or relativedistances of points of fixation.

A group distribution of visual resources, as shown in FIGS. 6A and 6B,may be determined or generated for any time, e.g., corresponding to atime of the dynamic visual stimulus. For example, a group distributionof visual resources may be generated at each sample time (e.g.,according to sample rate of eye data). Alternatively, select times maybe used, such as times corresponding to times or frames of interest inthe visual stimulus.

The system according to the present invention further includes softwarefor generating a display of the group's distribution of visual resourcesto the visual stimulus. FIGS. 7A-7H show an example of a means by whichto generate a display of the group's distribution of visual resourcesaccording to the present invention. FIG. 7A shows two-dimensionalrepresentations of a group of ten individuals' distribution of visualresources (e.g., 702) at particular times in response to a visualstimulus. In FIG. 7B, the distributions are displayed topographically(e.g., 704) over the same period of time. As will be apparent to oneskilled in the art upon reading the present description, the group'sdistribution of visual resources is changing over the exemplary periodof time (i.e., from left to right) from divergent to convergent (e.g.,identifying an area of heightened attention). FIG. 7C shows the group'sdistribution of visual resources at each time and a plane (e.g., 706) atan average (e.g., mean or median) value of relative salience or heightvalue.

FIG. 7D shows each plane (e.g. 706) and an area of maximal salience(e.g., 708) provided by the plane at each time. FIGS. 7E and 7F furthershow the areas of maximal salience (e.g., 708) at any number of times.To generate a preferred display of the group's distribution of visualresources according to the present invention, the areas may be connectedand/or extruded to develop an attentional funnel 750 over the period oftime as shown in FIG. 7G. The funnel 750 may be mapped to the visualstimulus and portions (e.g., frame 752) of the visual stimulus includedin the display to show the areas of the visual stimulus which correspondto the areas of maximal salience. As shown, a convergence is shown atthe frame 752 indicating an area of heightened attention to the eyes ofthe male actor. FIG. 7H shows the frame 752 as well as two precedingframes leading up to the convergence.

FIGS. 8A and 8B show two exemplary two-dimensional displays according tothe present invention. As shown, a portion 810 of a visual stimulus maybe displayed simultaneously with a display 820 of one or more areas ofmaximal salience, e.g., 822-828, determined as described above. Thedistribution of visual resources within the area may be represented by acolor gradient or pseudo-color mapping. In some embodiments, thedistribution is shown as an overlay to the visual stimulus wherein agrayscale from black to transparent represents relative salience (notshown). The display 820 may be static and depicting one particular timeof the eye data sampling synchronized to the particular portion 710(e.g., time and/or frame) of the visual stimulus. The display of thegroup's distribution of visual resources and/or attention may also bedynamic, e.g., showing the dynamic visual display and correspondingareas of maximal salience changing over time.

FIGS. 9A-9C show screenshots of a preferable display 900 of a group'sdistribution of visual resources to a visual stimulus according to thepresent invention. Shown in FIG. 9A, the display 900 may include anx-axis 910, y-axis 920 and a time axis 930. The display 900 may begenerated by connecting or extruding the areas of maximal salience overtime to create an attentional funnel 950 as described with reference toFIGS. 7A-7H. The funnel 950 may be synchronized with corresponding times(e.g., frame 932) of a dynamic visual stimulus. For static stimuli, anynumber of representations of the visual stimulus may similarly beincluded in the display to depict the corresponding areas of maximalsalience and/or heightened attention over time. The display 900 is alsopreferably a dynamic and/or streaming display. For example, the display900 may include an attentional funnel 950 streaming through all or aportion of a dynamic visual stimulus (e.g., video). Likewise, thedisplay 900 may include an attentional funnel 950 streaming through anynumber of representations (e.g., duplicate representations) of a staticvisual stimulus (e.g., print ad, painting, etc) over a period of time.

As shown in FIG. 9A, divergences (e.g., 952) of the group's visualresources, indicated by a widening of the funnel 950, and convergences(e.g., 954) of visual resources, indicated by a narrowing of the funnel950, are readily apparent from the attentional funnel 950. Therefore,regions of interest and/or areas of heightened visual salience and/orattention to the visual stimulus may be identified at the convergences.As will be apparent to those of skill in the art, the present inventiontherefore provides a means to determine distinct instances of attentionto a particular location at a particular time by a group of people,i.e., as revealed through the convergence of the attentional funnel 950.

FIG. 9B shows another screenshot of the display 900 according to thepresent invention. In this particular figure, an area of maximalsalience 960 is shown at a time 934 and represented as a cross-sectionof the attentional funnel 950. FIG. 9C shows another screenshot of thedisplay 900 in which a large divergence of visual resources 956 isrepresented. FIG. 9C further shows an area of maximal salience 962 at atime 938. In some embodiments, the display 900 may include a viewlooking through the area of maximal salience 962 (e.g., through thefunnel) at a particular time 938 or over time. For example, the displaymay be a dynamic display including a “fly through” display through thefunnel 950 wherein the area of maximal salience may be viewedcontinuously over time as shown in FIG. 9D.

The displays (e.g., 900) of the present invention may be generated for asample group of individuals, e.g., to determine a group's distributionof visual resources and/or attention to a particular visual stimulus.The displays according to the present invention may further be used tocompare one individual's ocular responses and/or distribution of visualresources with reference to the distribution of visual resources of acontrol group (e.g., typical responses). The responses and/ordistribution of visual resources of two different groups of individualsmay also be compared to one another. For example, the present inventionmay be used to compare the distribution of visual resources of one groupof a particular age, IQ, capacity, gender, consumer bracket, ethnicity,or any other demographic characteristic. The present invention may alsobe used to evaluate and/or diagnose an individual based upon theirresponses and/or relative scanpath and/or distribution of visualresources to a dynamic or static visual stimulus with reference to anattentional funnel based on a collection of typical responses to thevisual stimulus.

FIGS. 10A-10F shows a means by which to quantify statisticallysignificant convergences in visual scanning. FIG. 10A shows individualscan paths (e.g., 1002, 1004) of ten typically-developing individualsviewing the same visual stimulus. As shown in the scan paths of FIG.10A, and the corresponding attentional funnel 1010 of FIG. 10B, thegroup's distribution of visual resources and/or attention may convergeat particular times (e.g., 1012). To quantify the significance of theconvergence, the average or median value of relative salience may firstbe determined at each of any number of times (e.g., as described withreference to FIGS. 6B and 7C). FIG. 10C shows the median values ofrelative salience for the group of viewers plotted over time.

To determine when a convergence of a funnel is statisticallysignificant, the group's median values of relative salience may then becompared to simulated random data (e.g., for 100,000 possiblecombinations of points of regard for 10 individuals or viewers). Forexample, a histogram of possible median values or heights of relativesalience and an empirical cumulative distribution function for that setof values may be generated from the simulated data as shown in FIG. 10D.A probability of obtaining each median value of relative salience maythen be calculated and displayed as shown in FIG. 10E. A probability (p)may then be selected to define when a convergence is statisticallysignificant, i.e., when probability values exceed what could expected bychance. For example, a threshold of p<0.001 may be used. As shown inFIGS. 10E and 10F, this threshold of probability is met between a time1030 and a time 1032. Therefore, the convergence between time 1030 and1032 is statistically significant and indicates a location and time ofheightened attention.

FIGS. 11A-11F show a means by which to compare a group's distribution ofvisual resources to an individual's ocular responses. FIG. 11A shows ascreenshot of a display of several individual's points of regard and/orscan paths (e.g., 1140, 1142) over time. In the present example, the twogroups of individuals are represented. A first group (e.g., controlgroup) is indicated by black scan paths (e.g., 1140) and a second groupby gray scan paths (e.g., 1142). Shown in FIG. 11B, an attentionalfunnel 1160 is created from the first group's data. As shown, eachgroup's distribution of visual resources is divergent at a time 1150.However at a time 1152, the first group's distribution of visualresources converges, while the second group does not.

FIG. 11C shows a plot of the median values of relative salience for thefirst group 1170 compared to those of the second group 1172. In thepresent example, the first group 1170 represents a group having typicaldistributions of visual resources for a particular age and IQ levelwhile the second group 1172 represents a group of autistic individualsat the same age and IQ level. The demographics of each group may beknown prior to comparison, or in some cases, the present invention maybe used to subtype demographics quantitatively. The differences betweenthe first group and the second group may further be illustrated using adifference waveform 1174, shown in FIG. 11D, which depicts thedifference between each plot of median values 1170 and 1172 over time. Aplot 1176 of the significance of difference as probability (p) valuesmay also be generated as shown in FIG. 11E. In some embodiments, thedifferences are further quantified by comparison of gradient vectors ofsalience (e.g., for an individual or group) at one or more points intime.

FIG. 11F shows a display including a frame of the visual stimuluscorresponding to the time 1152 at which the visual resources of thefirst group converges. An area of maximal salience 1180 of the firstgroup is shown and indicates an area of heightened attention for thefirst group. As shown, points of regard (e.g., 1182) of the second groupfall outside of the area of maximal salience 1180 of the first group.The sequence illustrated in FIGS. 11A-11F demonstrates an example of theadvantageous measure and sensitivity of the system according to thepresent invention.

FIG. 12 shows a method of quantifying and mapping visual salienceaccording to the present invention. The method includes a first step1202 of receiving data indicative of a group of individual's ocularresponses to a visual stimulus (e.g., static or dynamic). The data maybe received from one or more eye trackers 110. Individual distributionsof visual resources may then be determined at each time and for eachindividual from which data is sampled (step 1204). As described above,determining a distribution of visual resources may include receivingand/or determining a distribution of retinal cells or other indices ofbiological resources. An average effective distribution of retinal cellsmay be used for each individual. Alternatively, an effectivedistribution of retinal cells may be determined or estimated for eachindividual that is sampled.

In step 1206, a group distribution of visual resources is determined.The group distribution of visual resources may be determined asdescribed above. For example, the individual distributions of visualresources may be summed or otherwise aggregated and an average value ofrelative salience or attention determined at each time. Areas of maximalsalience may be determined to represent the group's distribution ofvisual resources at each time based on the average value. As describedabove, convergences or decreased areas of maximal salience provideindication of heightened attention to the corresponding area of thevisual stimulus.

In step 1208, a display of the group's distribution of visual resourcesto the visual stimulus over time is generated. The group's distributionof visual resources and/or areas of maximal salience may then be mappedto the visual stimulus (step 1210). For example, the group distributiondetermined for each time (e.g., data sample time) may be mapped to aparticular frame of a video visual stimulus. For a static visualstimulus, each group distributions may similarly be mapped to the staticstimulus (or duplicate representations thereof). The group's areas ofmaximal salience and/or attention at each time may be connected orextruded over time to create an attentional funnel (e.g., 950). Portionsof the visual stimulus may be included in the display to provide avisual presentation of corresponding areas of maximal salience in thevisual stimulus over time.

To compare a subject individual to a group, the method may includereceiving subject data indicative of a subject's ocular responses to thesame dynamic visual stimulus and determining points of regard for thesubject. A display of points of regard (e.g., scanpath and/or individualattentional funnel) may be generated and compared to the display of thegroup's distribution of visual resources to the visual stimulus asdescribed above with reference to FIGS. 11A-11F.

Advantages of the present invention include the provision of abiologically-based means of quantification of viewing patterns todynamic and static visual stimuli and a means to quantify viewingpatterns to visual stimuli in which regions-of-interest over time aredetermined by the viewers.

Further advantages include the provision of a system and method todetermine statistically and behaviorally verifiable quantification ofepisodes of focused attention for groups of people to particular spatialand temporal locations of both static and dynamic visual stimuli.Further provided is a means to measure relative salience and absolutesalience.

The present invention further provides a system and method toquantitatively compare one individual against a group, one group againstanother group, and to quantitatively using the similarity of individualsto split one large group into smaller groups.

The present invention further provides unique means to visualize andgraphically represent ocular response data including, e.g., the obliquepresentation of data having an axis of time, continuous representationsof salience maps, attentional funnels, and views through attentionalfunnels. The visualization methods of the present invention provideunique means to visualize and determine statistically significantconvergences and episodes of focused visual attention.

Although the invention has been described with reference to a particulararrangement of parts, features and the like, these are not intended toexhaust all possible arrangements or features, and indeed manymodifications and variations will be ascertainable to those of skill inthe art.

What is claimed is:
 1. A method for diagnosing an individual, comprisingthe steps of: receiving data indicative of each member of a controlgroup's ocular responses to a visual stimulus that changes over time;receiving data indicative of the individual's ocular responses to thevisual stimulus; generating, via software executing on a processor, athree-dimensional scanpath based on the response data for each of themembers of the control group and for the individual, wherein two of thedimensions of the scanpath correspond to a position of a point of regardfor each of the members and the individual and one of the dimensionscorresponds to time; identifying, via software executing on theprocessor, a convergence of the scanpaths of the members of the controlgroup; and comparing, via software executing on the processor, thescanpath of the individual to the scanpaths of the members of thecontrol group in the region of the convergence.
 2. The method of claim1, wherein the method comprises assessing whether the individual isautistic.
 3. The method of claim 1, wherein the step of identifying aconvergence comprises determining whether the convergence isstatistically significant by comparing the response data of the membersof the control group with simulated random ocular response data.
 4. Themethod of claim 1, wherein the step of comparing the scanpath of theindividual to the scanpaths of the members of the control group furthercomprises identifying a divergence of the scanpath of the individualfrom the scanpaths of the members of the control group.
 5. The method ofclaim 1, further comprising the step of generating, via softwareexecuting on the processor, a display of the scanpaths in athree-dimensional grid comprising two positional axes and one time axis.6. The method of claim 5, further comprising the step of displaying anattentional funnel around the scanpaths of the members of the controlgroup.
 7. The method of claim 5, further comprising the step ofdisplaying, via software executing on the processor, a frame of thevisual stimulus in the grid positioned on the time axis so as tocorrespond with the ocular responses of the members of the control groupand the individual to the frame.
 8. The method of claim 1, wherein saidstep of displaying the scanpaths further comprises streaming thescanpaths to show the progression of the scanpaths as the time axisadvances with time.
 9. A method for evaluating at least one autisticindividual, comprising the steps of: receiving data indicative of eachmember of a control group's ocular responses to a visual stimulus thatchanges over time; receiving data indicative of the at least oneautistic individual's ocular responses to the visual stimulus;determining, via software executing on a processor, a first distributionof visual resources of the members of the control group with respect toat least a portion of the visual stimulus based on the group's ocularresponse data; determining, via software executing on the processor, asecond distribution of visual resources of the at least one autisticindividual with respect to the portion of the visual stimulus based onthe at least one individual's ocular response data; identifying, viasoftware executing on the processor, a convergence of the firstdistribution of visual resources of the members of the control group;and comparing, via software executing on the processor, the seconddistribution of visual resources of the at least one autistic individualto the first distribution of visual resources of the members of thecontrol group in the region of the convergence.
 10. The method of claim9, wherein the step of identifying a convergence comprises: determiningwhether the convergence is statistically significant by comparing theresponse data of the members of the control group with simulated randomocular response data.
 11. The method of claim 9, wherein the step ofidentifying a convergence comprises: calculating, via software executingon the processor, a calculated average value of relative salience forthe members of the control group; generating, via software executing onthe processor, a set of possible average values of relative saliencefrom a set of simulated salience data; calculating, via softwareexecuting on the processor, a probability of obtaining each of the setof possible average values of relative salience; selecting a probabilitythreshold below which an average value of relative salience hasstatistical significance; comparing, via software executing on theprocessor, the calculated average value of relative salience for themembers of the control group to the set of possible average values ofrelative salience; and determining whether the probability associatedwith the calculated average value of relative salience is below theprobability threshold.
 12. The method of claim 9, wherein said steps ofdetermining the first and second distributions of visual resourcescomprise calculating an effective distribution of retinal cells for eachmember of the control group and the at least one autistic individual.13. The method of claim 12, further comprising the step of: determininga density of cells relative to a unit of viewing angle for theindividual based on the individual's field-of-view.
 14. The method ofclaim 9, further comprising the step of generating, via softwareexecuting on the processor, a display of the first distributions ofvisual resources of the members of the control group and the seconddistribution of visual resources of the at least one autistic individualin a three-dimensional grid comprising two positional axes and one of atime axis or an axis representing a value of relative salience.
 15. Themethod of claim 14, wherein the three-dimensional grid comprises a timeaxis and the method further comprises the step of displaying a frame ofthe portion of the visual stimulus in the grid positioned on the timeaxis so as to correspond with the first and second distributions ofvisual resources corresponding to the frame.
 16. The method of claim 14,wherein the three-dimensional grid comprises a time axis and the methodfurther comprises the step of displaying an attentional funnelcorresponding to the first distributions of visual resources of themembers of the control group.
 17. The method according to claim 12,wherein said step of determining the first distribution of visualresources of the members of the control group comprises aggregating theindividual distributions of visual resources of each of the members ofthe control group by linearly summing or multiplying.